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    Estimation of Induction Motor Parameters Using Hybrid Algorithms for Power System Dynamic Studies

    Access Status
    Fulltext not available
    Authors
    Susanto, Julius
    Islam, Syed
    Date
    2013
    Type
    Conference Paper
    
    Metadata
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    Citation
    Susanto, Julius and Islam, Syed. 2013. Estimation of Induction Motor Parameters Using Hybrid Algorithms for Power System Dynamic Studies, in Negnevitsky, M. (ed), Proceedings of the Australasian Universities Power Engineering Conference (AUPEC), Sep 29-Oct 3 2013. Hobart, Tasmania: University of Tasmania.
    Source Title
    Proceedings of the 2013 Australasian Universities Power Engineering Conference
    Source Conference
    2013 Australasian Universities Power Engineering Conference
    DOI
    10.1109/AUPEC.2013.6725462
    ISBN
    9781862959132
    URI
    http://hdl.handle.net/20.500.11937/23117
    Collection
    • Curtin Research Publications
    Abstract

    This paper proposes a hybrid Newton-Raphson and genetic algorithm for the estimation of double cage induction motor parameters from commonly available manufacturer data. The hybrid algorithm was tested on a large data set of 6,380 IEC and NEMA motors and then compared with a baseline Newton-Raphson algorithm. The simulation results show that while the proposed hybrid algorithm is more computationally intensive, it does make significant improvements to convergence and error rates.

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